Cemented Versus Uncemented Reverse Shoulder Arthroplasty Treatment of Proximal Humerus Fractures: National Shoulder Arthroplasty Data from Türkiye.

Background: This study evaluated national trends in cemented and uncemented reverse shoulder arthroplasty (RSA) for proximal humerus fractures using a comprehensive national surgical database. This study aimed to compare RSA used in the treatment of proximal humerus fractures with the literature and to determine the country's trend. Methods: A cross-sectional study was conducted using the health records of individuals aged ≥ 18 years who underwent RSA for proximal humerus fractures between 2016 and 2022. Patients were divided into cemented and uncemented groups, and demographic data (age, sex), duration of hospital stay, transfusions, revisions, mortality, and Charlson Comorbidity Index (CCI) scores were analyzed. Results: A total of 618 cemented RSA and 1,364 uncemented RSA procedures were reviewed. Patients who underwent cemented RSA were significantly older than those who had uncemented RSA (p = 0.002). Transfusion rates were higher in the cemented RSA group (p = 0.006). The frequency of revision surgery was 6.1%. Younger age and male sex were associated with revision (p < 0.001). CCI scores were higher among transfused patients than non-transfused patients (p < 0.001). The incidence of cemented RSA was 11.7% and 49% in 2016 and 2022, respectively. Differences were found among hospital types and geographical regions. Conclusions: While cemented RSA has been gaining attention and increased application in recent years for proximal humerus fractures, uncemented RSA still predominates. The choice between these 2 methods is largely influenced by regional and hospital-level factors. The type of RSA and high CCI scores were found to have no significant impact on the risk of surgical revision.

Analysis of postoperative weight loss associated with prognosis after sublobar resections for lung cancer.

OBJECTIVES: Sublobar resections for lung cancer are increasing worldwide. However, the prognostic significance of weight loss after sublobar resection remains unclear. We aimed to investigate the prognostic significance of weight loss after sublobar resection for lung cancer. METHODS: Patients who underwent sublobar resection for non-small cell lung cancer between January 2016 and June 2021 were analysed. The percentage weight change at 3, 6, and 12 months postoperatively was determined based on the preoperative weight. Patients were divided into two groups: those with or without weight loss ≥ 5%, referring to the diagnostic criteria for frailty, to assess prognosis. Subsequently, the prognosis-related timing of weight loss ≥ 5% and its risk factors were analyzed. RESULTS: We reviewed 147 patients; 39 (26.5%) showed weight loss ≥ 5% within 1-year post-surgery. A total of 32 patients (21.8%) died, 13 from primary lung cancer and 19 from non-lung cancer causes. Cancer recurrence occurred in 22 patients (15.0%). Weight loss ≥ 5% within 1-year post-surgery was a poor prognostic factor for overall and recurrence-free survival (log-rank; p = 0.014 and 0.018, respectively). Additionally, weight loss ≥ 5% at 6-12 months postoperatively was associated with poor overall and recurrence-free survival (p < 0.05, both). In the multivariable analysis, an age-adjusted Charlson comorbidity index ≥ 4 was a predictive factor for weight loss ≥ 5% at 6-12 months postoperatively (odds ratio, 3.920; p = 0.023). CONCLUSIONS: Weight loss ≥ 5% at 6-12 months postoperatively was associated with poor prognosis. Long-term nutritional management is important in the treatment plan of sublobar resection in high-risk patients.

Long-term outcome following liver transplantation of patients with ACLF grade 3.

BACKGROUND AND AIMS: Utility, a major principle for allocation in the context of transplantation, is questioned in patients with acute-on chronic liver failure grade 3 (ACLF-3) who undergo liver transplantation (LT). We aimed to explore long-term outcomes of patients included the three-center retrospective French experience published in 2017. METHOD: All patients with ACLF-3 (n=73) as well as their transplanted matched controlled with ACLF-2 (n=145), 1 (n=119) and no ACLF (n=292) that have participated in the princeps study published in 2017 were included. We explored 5- and 10-year patient and graft survivals, causes of death and their predictive factors. RESULTS: Median follow-up of patients ACLF-3 patients was 7.5 years. At LT, median MELD was 40. In patients with ACLF-3, 2, 1 and no ACLF, 5-year patients' survivals were respectively 72.6% vs. 69.7% vs. 76.4% vs. 77.0% (p=0.31). Ten-year patients' survival ACLF-3 was 56.8% and was not different other groups (p=0.37) Leading causes of death in ACLF-3 patients were infections (33.3%), and cardiovascular events (23.3%). After exclusion of early death, UCLA futility risk score, age-adjusted Charlson comorbidity index and Chronic Liver Failure Consortium ACLF score were independently associated with 10-year patients' survival. Long-term grafts' survivals were not different across the groups. Clinical frailty scale and WHO performance status improved over time in patients alive after 5 years. CONCLUSION: 5- and 10-year patients' and grafts' survivals in ACLF-3 patients were not different from their controls. 5-year patients' survival is higher than that of the 50%-70% threshold defining the utility of liver graft. Efforts should focus on candidates' selection based on comorbidities as well as the prevention of infection and cardiovascular events standing as the main cause of death. IMPACT AND IMPLICATIONS: While short-term outcomes following liver transplantation in the most severely ill cirrhotic patients (ACLF-3) are known, long-term data are limited, raising questions about the utility of graft allocation in the context of scarce medical resources. This study provides a favorable long-term update, confirming no differences in 5- and 10-year patient and graft survival following liver transplantation in ACLF-3 patients compared to matched ACLF-2, ACLF-1, and no-ACLF patients. The study highlights the risk of dying from infection and cardiovascular causes in the long-term and identifies scores including comorbidities evaluation, such as the age-adjusted Charlson Comorbidity Index, as independently associated with long-term survival. Therefore, physicians should consider the cumulative burden of comorbidities when deciding to transplant these patients. Additionally, after transplantation, the study encourages mitigating infectious risk with tailored immunosuppressive regimens and managing tightly cardiovascular risk over time.

The Chronicles of Comorbidity and Cancer Care.

Care for patients with cancer is more challenging when they have concurrent, complex comorbidities. Risk assessment tools may help to enhance care assessment and predict poor clinical outcomes for these patients. This article.

Combined Charlson comorbidity/C-Reactive Protein Index Is a Novel Predictor in Renal Cell Carcinoma: Analysis of the International Marker Consortium for Renal Cancer (INMARC) Registry.

OBJECTIVE: To evaluate predictive ability of a novel combined index, Charlson comorbidity index and C-reactive protein (CCI-CRP), for outcomes in renal cell carcinoma (RCC), and compare predictive outcomes with of CCI-CRP to its separate components and to the UCLA integrated staging system (UISS). PATIENTS AND METHODS: We retrospectively analyzed INMARC registry of RCC patients. Receiver Operator Characteristics (ROC) analysis was fitted to identify threshold defining low-CRP (LCRP) and high-CRP (HCRP). Patients were stratified according to CCI [low-CCI ≤ 3 (LCCI); intermediate-CCI 4-6 (ICCI); high-CCI > 6 (HCCI)] and CRP level. Kaplan-Meier analysis (KMA) was conducted for overall (OS) and cancer-specific survival (CSS). Based on survival analysis distribution we proposed a new stratification: CCI-CRP. Model performance was assessed with ROC/area under the curve (AUC) analysis and compared to CCI and CRP alone, and UISS. RESULTS: We analyzed 2,890 patients (median follow-up 30 months). ROC identified maximum product sensitivity and specificity for CRP at 3.5 mg/L. KMA revealed 5-year OS of 95.6% for LCRP/LCCI, 83% LCRP/ICCI, 73.3% LCRP/HCCI, 62.6% HCRP/LCCI, 51.6% HCRP/ICCI and 40.5% HCRP/HCCI (P < .001). From this distribution, new CCI-CRP is proposed: low CCI-CRP (LCRP/LCCI and LCRP/ICCI), intermediate CCI-CRP (LCRP/HCCI and HCRP/LCCI), and high CCI-CRP (HCRP/ICCI and HCRP/HCCI). AUC for CCI-CRP showed improved performance for predicting OS/CSS vs. CCI alone (0.73 vs. 0.63/0.77 vs. 0.60), CRP alone (0.73 vs. 0.71/0.77 vs. 0.74) and UISS (0.73 vs 0.67/0.77 vs 0.73). CONCLUSIONS: CCI-CRP, exhibits increased prognostic performance for survival outcomes in RCC compared to CCI and CRP alone, and UISS. Further investigation is requisite.

Effect of polypharmacy on the outcomes of older patients with advanced non-small-cell lung cancer treated with PD-1/PD-L1 inhibitors: A retrospective cohort study.

INTRODUCTION: The effect of polypharmacy on older patients with cancer is unclear. This study aimed to explore the effect of polypharmacy on the outcomes of treatment in older patients with advanced non-small cell lung cancer (NSCLC) treated with PD-1/PD-L1 inhibitors. MATERIALS AND METHODS: We retrospectively reviewed the records of older patients (aged ≥65 years) with advanced NSCLC who received PD-1/PD-L1 inhibitors with or without platinum-based chemotherapy as first-line treatment from March 2016 to December 2020. Patients with driver oncogenes or Eastern Cooperative Oncology Group performance status (PS) ≥2 were excluded. Polypharmacy was defined as receiving five or more oral or inhaled medications at baseline. We compared the progression-free survival (PFS), overall survival (OS), and mean cumulative length of hospital stays between the polypharmacy and non-polypharmacy groups. RESULTS: A total of 122 patients, with a median age of 72 years (range, 65-89 years), were included in the analysis. Of the patients, 34 (27.8%) had a PS of 0 and 68 (55.7%) had a PD-L1 tumor proportion score (TPS) of ≥50%. The median number of oral or inhaled medications was 4 (range, 0-12), and 60 (49.1%) patients were taking ≥5 medications (polypharmacy). Age and Charlson Comorbidity Index score were significantly higher in the polypharmacy group (P = 0.01 and P < 0.001, respectively). Compared with the non-polypharmacy group, the polypharmacy group had a similar median PFS (6.7 vs. 8.5 months, P = 0.94) and a shorter median OS (17.3 vs. 26.0 months, P = 0.04). In the polypharmacy group, the adjusted hazard ratio for OS (adjusted for age, PS, and PD-L1 TPS) was 1.65 (95% confidence interval, 1.04-2.86, P = 0.03). Patients in the polypharmacy group had longer hospital stays (46.3 ± 7.5 vs. 27.7 ± 4.1 days/person, P < 0.05) and more emergency hospitalizations (1.6 ± 0.3 vs. 0.8 ± 0.1 times/person, P < 0.05) during the first year. DISCUSSION: Polypharmacy was associated with shorter survival time and longer hospitalization in older patients with advanced NSCLC receiving first-line immunotherapy with or without chemotherapy.

The Tumor Risk Score (TRS) - next level risk prediction in head and neck tumor surgery.

PURPOSE: Head and neck cancer surgery often requires postoperative monitoring in an intensive care unit (ICU) or intermediate care unit (IMC). With a variety of different risk scores, it is incumbent upon the investigator to plan a risk-adapted allocation of resources. Tumor surgery in the head and neck region itself offers a wide range of procedures in terms of resection extent and reconstruction methods, which can be stratified only vaguely by a cross-disciplinary score. Facing a variety of different risk scores we aimed to develop a new Tumor Risk Score (TRS) enabling anterograde preoperative risk evaluation, resource allocation and optimization of cost and outcome measurements in tumor surgery of the head and neck. METHODS: A collective of 547 patients (2010-2021) with intraoral tumors was studied to develop the TRS by grading the preoperative tumor size and location as well as the invasiveness of the planned surgery by means of statistical modeling. Two postoperative complications were defined: (1) prolonged postoperative stay in IMC/ICU and (2) prolonged total length of stay (LOS). Each parameter was analyzed using TRS and all preoperative patient parameters (age, sex, preoperative hemoglobin, body-mass-index, preexisting medical conditions) using predictive modeling design. Established risk scores (Charlson Comorbidity Index (CCI), American Society of Anesthesiologists risk classification (ASA), Functional Comorbidity Index (FCI)) and Patient Clinical Complexity Level (PCCL) were used as benchmarks for model performance of the TRS. RESULTS: The TRS is significantly correlated with surgery duration (p < 0.001) and LOS (p = 0.001). With every increase in TRS, LOS rises by 9.3% (95%CI 4.7-13.9; p < 0.001) or 1.9 days (95%CI 1.0-2.8; p < 0.001), respectively. For each increase in TRS, the LOS in IMC/ICU wards increases by 0.33 days (95%CI 0.12-0.54; p = 0.002), and the probability of an overall prolonged IMC/ICU stay increased by 32.3% per TRS class (p < 0.001). Exceeding the planned IMC/ICU LOS, overall LOS increased by 7.7 days (95%CI 5.35-10.08; p < 0.001) and increases the likelihood of also exceeding the upper limit LOS by 70.1% (95%CI 1.02-2.85; p = 0.041). In terms of predictive power of a prolonged IMC/ICU stay, the TRS performs better than previously established risk scores such as ASA or CCI (p = 0.031). CONCLUSION: The lack of a standardized needs assessment can lead to both under- and overutilization of the IMC/ICU and therefore increased costs and losses in total revenue. Our index helps to stratify the risk of a prolonged IMC/ICU stay preoperatively and to adjust resource allocation in major head and neck tumor surgery.

Blood Cancer Network Ireland (BCNI) and National Cancer Registry Ireland (NCRI) collaboration: challenges and utility of an Enhanced Blood Cancer Outcomes Registry (EBCOR) pilot.

BACKGROUND: The Blood Cancer Network Ireland and National Cancer Registry Ireland worked to create an Enhanced Blood Cancer Outcomes Registry (EBCOR). Enhanced data in acute myeloid leukaemia (AML) included an extensive data dictionary, bespoke software and longitudinal follow-up. AIMS: To demonstrate the utility of the database, we applied the data to examine a clinically relevant question: Charlson comorbidity index (CCI) usefulness in predicting AML patients' survival. METHODS: A software designer and consultant haematologists in Cork University Hospital worked together to standardise a data dictionary, train registrars and populate a database. One hundred and forty-one AML patients underwent enhanced data registration. Comorbidities identified by chart review were used to examine the capability of the CCI and age at diagnosis to predict mortality using Kaplan-Meier curves, Cox regression and receiver operating characteristic curves. RESULTS: In regression analysis, a dose-response relationship was observed; patients in the highest CCI tertile displayed a greater risk (HR = 4.90; 95% CI 2.79-8.63) of mortality compared to subjects in tertile 2 (HR = 2.74; 95% CI 1.64-4.57) and tertile 1 (reference). This relationship was attenuated in an analysis which adjusted for age at diagnosis. The area under the curve (AUC) for the CCI was 0.76 (95% CI 0.68-0.84) while the AUC for age at diagnosis was 0.84 (95% CI 0.78-0.90). CONCLUSIONS: Results suggest that the CCI provides no additional prognostic information beyond that obtained from age alone at AML diagnosis and that an EBCOR can provide a rich database for cancer outcomes research, including predictive models and resource allocation.

Prescription Medications and Overall Survival in Metastatic Hormone Sensitive Prostate Cancer.

BACKGROUND/AIM: With new therapies for metastatic prostate cancer, patients are living longer, increasing the need for better understanding of the impact of comorbid disease. Prescription medications may risk-stratify patients independent of established methods, such as the Charlson Comorbidity Index (CCI) and guide treatment selection. PATIENTS AND METHODS: In a nationwide retrospective study of US Veterans, we used multivariable logistic regression and Cox proportional hazard modeling to evaluate the association between number and class of prescription medications and overall survival (OS) with age, race, body-mass index, prostate specific antigen (PSA), and Charlson comorbidities as covariates in veterans treated for de novo metastatic hormone sensitive prostate cancer (mHSPC) between 2010-2021. RESULTS: Among 8,434 Veterans, a median of nine medications and five medication classes were filled in the year prior to initial treatment with abiraterone or enzalutamide for mHSPC. Veterans on 1-4 medications had an average survival of 38 months compared to 5-9 medicines (33 months), 10-14 medicines (27 months), and 15+ medicines (22 months) (p<0.001). After adjusting for age, race, body mass index (BMI), PSA, CCI, and year of diagnosis, both the number of medications and medication classes were associated with increased mortality. The adjusted hazard ratio (aHR) [95% confidence interval (CI)] was 1.03 (1.02-1.03) for the number of medications and 1.05 (1.04-1.07) for medication classes. Medications within ATC B (blood/blood forming organs), ATC C (cardiovascular), and ATC N (nervous) were associated with worse OS, with aHRs of 1.14 (1.07, 1.21), 1.14 (1.06, 1.22), and 1.12 (1.06, 1.19), respectively. CONCLUSION: The number and class of medications were independently associated with overall survival in patients undergoing treatment for mHSPC. With new therapies for advanced prostate cancer, patients are living longer, highlighting the need for a better understanding of the impact of comorbid diseases. Simple methods to assess disease burden and prognosticate survival have the potential to guide treatment decisions.

Impact of Smoking Cessation and Charlson Comorbidity Index on Influenza Vaccination Efficacy in COPD Patients.

Chronic obstructive pulmonary disease (COPD) patients are particularly susceptible to respiratory infections like influenza, which exacerbate symptoms and increase healthcare utilization. While smoking cessation and influenza vaccination are recommended preventive measures, their combined impact on healthcare resource utilization is underexplored. The Charlson Comorbidity Index (CCI) assesses comorbidity burden in COPD patients and may influence healthcare outcomes. We conducted a retrospective analysis of 357 COPD patients, evaluating smoking cessation success over one year and influenza vaccination receipt, stratifying patients by CCI scores. Healthcare utilization outcomes included emergency room visits, hospitalizations, and medical expenses. Results showed that 51.82% of patients quit smoking and 59.66% received influenza vaccination, with higher comorbidity prevalence in advanced COPD stages (p = 0.002). Both smoking cessation and influenza vaccination independently correlated with decreased emergency room visits, hospital admissions, days, and costs. Patients who both quit smoking and received influenza vaccination exhibited the lowest healthcare utilization rates. In conclusion, smoking cessation and influenza vaccination significantly reduce healthcare resource utilization in COPD patients, with the combination yielding synergistic benefits, particularly in those with lower CCI scores. Integrating these interventions and comorbidity management in COPD strategies is essential for optimizing patient outcomes and healthcare efficiency.

The impact of comorbidities on outcomes of concomitant mitral valve intervention with ascending aortic surgery.

INTRODUCTION: The Charlson Comorbidity Index (CCI) is widely utilized for risk stratification for non-cardiac surgical patients, yet it has not been broadly validated in patients undergoing cardiac surgery. We aim to assess its ability to predict early and late outcomes of concomitant mitral valve intervention with ascending aortic surgery. METHODS: Patients who underwent surgery between 1997 and 2022 were reviewed. Age-adjusted CCI scores were calculated based on clinical status at a time of index operation. The primary endpoint was all causes mortality while secondary outcomes were major adverse events (MAE) that included combined perioperative mortality, dialysis, myocardial infarction, and stroke in addition to the individual outcomes and take back for bleeding and tracheostomy. Chi-square test, Logistic and Cox regression analysis, and Kaplan-Meier curves were used. Maximally selected rank statistics were used to identify best cutoff of CCI for late mortality. RESULTS: 186 patients (median age 65 [interquartile range (IQR): 54-76] and 69% males) were included with a median CCI of 4 [IQR: 3-6]. Five and ten-years overall survival were 95.9% and 67.1% vs 59.7%, and 19.9% in CCI ≤ 5 vs >5 (P < 0.001). On multivariate Cox regression analysis, higher CCI (HR 1.60 [1.17;2.18], P = 0.00), and lower EF (HR 0.89 [0.83;0.96], P = 0.002) were associated with late mortality. There was a trend to lower mortality in recent surgery years (HR 0.91 [0.83;1.01], P = 0.070)). Perioperative MAE was higher in CCI >5 (11.0% vs 2.1%, P = 0.017), and postoperative need for tracheostomy and CVA had a trend to be higher in CCI > 5 (P = 0.055). Logistic regression revealed that higher CCI, as a continuous variable, was associated with significantly higher odds of MAE, postoperative dialysis, and need for tracheostomy. CONCLUSIONS: The CCI can be a helpful tool in predicting outcomes of patients undergoing concomitant mitral valve intervention with ascending aortic surgery.

Can We Go beyond Pathology? The Prognostic Role of Risk Scoring Tools for Cancer-Specific Survival of Patients with Bladder Cancer Undergoing Radical Cystectomy.

Radical cystectomy (RC) remains a mainstay surgical treatment for non-metastatic muscle-invasive and BCG-unresponsive bladder cancer. Various perioperative scoring tools assess comorbidity burden, complication risks, and cancer-specific mortality (CSM) risk. We investigated the prognostic value of these scores in patients who underwent RC between 2015 and 2021. Cox proportional hazards were used in survival analyses. Risk models' accuracy was assessed with the concordance index (C-index) and area under the curve. Among 215 included RC patients, 63 (29.3%) died, including 53 (24.7%) cancer-specific deaths, with a median follow-up of 39 months. The AJCC system, COBRA score, and Charlson comorbidity index (CCI) predicted CSM with low accuracy (C-index: 0.66, 0.65; 0.59, respectively). Multivariable Cox regression identified the AJCC system and CCI > 5 as significant CSM predictors. Additional factors included the extent of lymph node dissection, histology, smoking, presence of concomitant CIS, and neutrophil-to-lymphocyte ratio, and model accuracy was high (C-index: 0.80). The internal validation of the model with bootstrap samples revealed its slight optimism of 0.06. In conclusion, the accuracy of the AJCC staging system in the prediction of CSM is low and can be improved with the inclusion of other pathological data, CCI, smoking history and inflammatory indices.

Nomogram based on immune-inflammatory indicators and age-adjusted charlson comorbidity index score to predict prognosis of postoperative parotid gland carcinoma patients.

BACKGROUND: Parotid gland carcinoma (PGC) is a rare malignant tumor. The purpose of this study was to investigate the role of immune-inflammatory-nutrition indicators and age-adjusted Charlson comorbidity index score (ACCI) of PGC and develop the nomogram model for predicting prognosis. METHOD: All patients diagnosed with PGC in two tertiary hospitals, treated with surgical resection, from March 2012 to June 2018 were obtained. Potential prognostic factors were identified by univariate and multivariate Cox regression analyses. The nomogram models were established based on these identified independent prognostic factors. The performance of the developed prognostic model was estimated by related indexes and plots. RESULT: The study population consisted of 344 patients with PGC who underwent surgical resection, 285 patients without smoking (82.8%), and 225 patients (65.4%) with mucoepidermoid carcinoma, with a median age of 50.0 years. American Joint Committee on Cancer (AJCC) stage (p < 0.001), pathology (p = 0.019), tumor location (p < 0.001), extranodal extension (ENE) (p < 0.001), systemic immune-inflammation index (SII) (p = 0.004), prognostic nutrition index (PNI) (p = 0.003), ACCI (p < 0.001), and Glasgow prognostic Score (GPS) (p = 0.001) were independent indicators for disease free survival (DFS). Additionally, the independent prognostic factors for overall survival (OS) including AJCC stage (p = 0.015), pathology (p = 0.004), tumor location (p < 0.001), perineural invasion (p = 0.009), ENE (p < 0.001), systemic immune-inflammation index (SII) (p = 0.001), PNI (p = 0.001), ACCI (p = 0.003), and GPS (p = 0.033). The nomogram models for predicting DFS and OS in PGC patients were generated based on these independent risk factors. All nomogram models show good discriminative capability with area under curves (AUCs) over 0.8 (DFS 0.802, and OS 0.825, respectively). Decision curve analysis (DCA), integrated discrimination improvement (IDI), and net reclassification index (NRI) show good clinical net benefit of the two nomograms in both training and validation cohorts. Kaplan-Meier survival analyses showed superior discrimination of DFS and OS in the new risk stratification system compared with the AJCC stage system. Finally, postoperative patients with PGC who underwent adjuvant radiotherapy had a better prognosis in the high-, and medium-risk subgroups (p < 0.05), but not for the low-risk subgroup. CONCLUSION: The immune-inflammatory-nutrition indicators and ACCI played an important role in both DFS and OS of PGC patients. Adjuvant radiotherapy had no benefit in the low-risk subgroup for PGC patients who underwent surgical resection. The newly established nomogram models perform well and can provide an individualized prognostic reference, which may be helpful for patients and surgeons in proper follow-up strategies.

The Effect of the Charlson Comorbidity Index On In-Hospital Complications, Hospital Length of Stay, Mortality, and Readmissions Among Patients Hospitalized for Acute Stroke.

Aim A notable number of people who develop stroke have comorbid medical conditions. The aim of this study is to evaluate the use of the Charlson Comorbidity Index (CCI) to predict in-hospital complications, mortality, length of stay, and readmission rates in stroke patients. Method It is a retrospective study that analyzed patients who were admitted for stroke in a six-month time duration. Stroke was classified into ischemic, hemorrhagic, or undetermined; hospital complications were classified into medical or neurological. Data regarding comorbidities, complications, length of stay, mortality, and readmissions were documented. Comorbidities were then classified by the CCI and split into four categories: zero, mild (1-2), moderate (3-4) and severe (5+). The data was analyzed using SPSS (IBM, Inc., Armonk, US). Results Four hundred and seventy-three adults aged above 18 were hospitalized for acute stroke. There was no correlation between the severity of the CCI score and mortality. Patients with ischemic stroke had a higher CCI correlated with readmission rate (p=0.026) and hospital complications (p=0.054). The two groups with the highest intensive care unit admission rate were mild, followed by the severe group (p=0.001). Our study also revealed that the patients with severe CCI scores had an increased readmission rate (p=0.001). Conclusion There is a correlation between a high CCI score and readmission rate, as well as CCI score with hospital complications in ischemic stroke. Further prospective studies of a longer duration can be undertaken to find further associations with the potential for this score to be used as a predictor in patients hospitalized for stroke.

Prognostic value and association of the age-adjusted Charlson Comorbidity Index with sarcopenia within patients with gastric cancer after radical resection.

PURPOSE: The association between the age-adjusted Charlson Comorbidity Index (ACCI) and sarcopenia in patients with gastric cancer (GC) remains ambiguous. This study aimed to investigate the association between the ACCI and sarcopenia and the prognostic value in patients with GC after radical resection. In addition, this study aimed to develop a novel prognostic scoring system based on these factors. METHODS: Univariate and multivariate Cox regression analyses were used to determine prognostic factors in patients undergoing radical GC resection. Based on the ACCI and sarcopenia, a new prognostic score (age-adjusted Charlson Comorbidity Index and Sarcopenia [ACCIS]) was established, and its prognostic value was assessed. RESULTS: This study included 1068 patients with GC. Multivariate analysis revealed that the ACCI and sarcopenia were independent risk factors during the prognosis of GC (P = 0.001 and P < 0.001, respectively). A higher ACCI score independently predicted sarcopenia (P = 0.014). A high ACCIS score was associated with a greater American Society of Anesthesiologists score, higher pathologic TNM (pTNM) stage, and larger tumor size (all P < 0.05). Multivariate analysis demonstrated that the ACCIS independently predicted the prognosis for patients with GC (P < 0.001). By incorporating the ACCIS score into a prognostic model with sex, pTNM stage, tumor size, and tumor differentiation, we constructed a nomogram to predict the prognosis accurately (concordance index of 0.741). CONCLUSION: The ACCI score and sarcopenia are significantly correlated in patients with GC. The integration of the ACCI score and sarcopenia markedly enhances the accuracy of prognostic predictions in patients with GC.

Charlson and Elixhauser Comorbidity Indices for Prediction of Mortality and Hospital Readmission in Patients With Acute Pulmonary Embolism.

Several risk stratification systems aid clinicians in classifying pulmonary embolism (PE) severity and prognosis. We compared 2 clinical PE scoring systems, the PESI and sPESI scores, with 2 comorbidity indices, the Charlson Comorbidity Index (CCI) and the val Walraven Elixhauser Comorbidity Index (ECI), to determine the utility of each in predicting mortality and hospital readmission. Information was collected from 436 patients presenting with PE via retrospective chart review. The PESI, sPESI, CCI, and ECI scores were calculated for each patient. Multivariate analysis was used to determine each system's ability to predict in-hospital mortality, 90-day mortality, overall mortality, and all-cause hospital readmission. The impact of various demographic and clinical characteristics of each patient on these outcomes was also assessed. The PESI score was found to be an independent predictor of in-hospital mortality and 90-day mortality. The PESI score and the CCI were able to independently predict overall mortality. None of the 4 risk scores independently predicted hospital readmission. Other factors including hypoalbuminemia, serum BNP, coagulopathy, anemia, and diabetes were associated with increased mortality and readmission at various endpoints. The PESI score was the best tool for predicting mortality at any endpoint. The CCI may have utility in predicting long-term outcomes. Further work is needed to better determine the roles of the CCI and ECI in predicting patient outcomes in PE. The potential prognostic implications of low serum albumin and anemia at the time of PE also warrant further investigation.

Characteristics of Comorbid Physical Disease in Patients With Severe Mental Illness in South Korea: A Nationwide Population-Based Study (2014-2019).

OBJECTIVE: The purpose of this study was to identify the associations of chronic physical disease between patients with severe mental illness (SMI) and the general population of South Korea. METHODS: This study was conducted with National Health Insurance Corporation data from 2014 to 2019. A total of 848,058 people were diagnosed with SMI in this period, and the same number of controls were established by matching by sex and age. A descriptive analysis was conducted on the sociodemographic characteristics of patients with SMI. Conditional logistic regression analysis was performed to identify the associations between comorbid physical disease in patients with SMI and those of the general population. SAS Enterprise Guide 7.1 (SAS Inc, Cary, NC, USA) were used to perform all statistical tests. RESULTS: The analysis revealed significant differences in medical insurance, income level, and Charlson Comorbidity Index weighted by chronic physical disease, between patients with SMI and the general population. Conditional logistic regression analysis between the two groups also revealed significant differences in eight chronic physical diseases except hypertensive disease. CONCLUSION: This study confirmed the vulnerability of patients with SMI to chronic physical diseases and we were able to identify chronic physical disease that were highly related to patients with SMI.

Age-adjusted Charlson comorbidity index is associated with the risk of osteoporosis in older fall-prone men: a retrospective cohort study.

BACKGROUND: There is growing evidence linking the age-adjusted Charlson comorbidity index (aCCI), an assessment tool for multimorbidity, to fragility fracture and fracture-related postoperative complications. However, the role of multimorbidity in osteoporosis has not yet been thoroughly evaluated. We aimed to investigate the association between aCCI and the risk of osteoporosis in older adults at moderate to high risk of falling. METHODS: A total of 947 men were included from January 2015 to August 2022 in a hospital in Beijing, China. The aCCI was calculated by counting age and each comorbidity according to their weighted scores, and the participants were stratified into two groups by aCCI: low (aCCI < 5), and high (aCCI ≥5). The Kaplan Meier method was used to assess the cumulative incidence of osteoporosis by different levels of aCCI. The Cox proportional hazards regression model was used to estimate the association of aCCI with the risk of osteoporosis. Receiver operating characteristic (ROC) curve was adapted to assess the performance for aCCI in osteoporosis screening. RESULTS: At baseline, the mean age of all patients was 75.7 years, the mean BMI was 24.8 kg/m2, and 531 (56.1%) patients had high aCCI while 416 (43.9%) were having low aCCI. During a median follow-up of 6.6 years, 296 participants developed osteoporosis. Kaplan-Meier survival curves showed that participants with high aCCI had significantly higher cumulative incidence of osteoporosis compared with those had low aCCI (log-rank test: P < 0.001). When aCCI was examined as a continuous variable, the multivariable-adjusted model showed that the osteoporosis risk increased by 12.1% (HR = 1.121, 95% CI 1.041-1.206, P = 0.002) as aCCI increased by one unit. When aCCI was changed to a categorical variable, the multivariable-adjusted hazard ratios associated with different levels of aCCI [low (reference group) and high] were 1.00 and 1.557 (95% CI 1.223-1.983) for osteoporosis (P <  0.001), respectively. The aCCI (cutoff ≥5) revealed an area under ROC curve (AUC) of 0.566 (95%CI 0.527-0.605, P = 0.001) in identifying osteoporosis in older fall-prone men, with sensitivity of 64.9% and specificity of 47.9%. CONCLUSIONS: The current study indicated an association of higher aCCI with an increased risk of osteoporosis among older fall-prone men, supporting the possibility of aCCI as a marker of long-term skeletal-related adverse clinical outcomes.

Impact of Charlson Comorbidity Index on in-hospital mortality of patients with hyperglycemic crises: A propensity score matching analysis.

AIM: This study was designed to investigate the association between Charlson Comorbidity Index (CCI) and in-hospital mortality and other clinical outcomes among patients with hyperglycemic crises. METHOD: This retrospective cohort study was conducted using data from electric medical records. A total of 1668 diabetic patients with hyperglycemic crises from six tertiary hospitals met the inclusion criteria. CCI < 4 was defined as low CCI and CCI ≥ 4 was defined as high CCI. Propensity score matching (PSM) with the 1:1 nearest neighbour matching method and the caliper value of 0.02 was used to match the baseline characteristics of patients with high CCI and low CCI to reduce the confounding bias. In-hospital mortality, ICU admission, hypoglycemia, hypokalemia, acute kidney injury, length of stay (LOS), and hospitalisation expense between low CCI and high CCI were compared and assessed. Univariate and multivariate regression were applied to estimate the impact of CCI on in-hospital and other clinical outcomes. OUTCOME: One hundred twenty-one hyperglycemic crisis (HC) patients died with a mortality rate of 7.3%. After PSM, compared with low CCI, patients with high CCI suffered higher in-hospital mortality, ICU admission, LOS, and hospitalisation expenses. After multivariate regression, age (aOR: 1.12, 95% confidence interval [CI]: 1.06-1.18, p < 0.001), CCI(aOR: 4.42, 95% CI: 1.56-12.53, p = 0.005), uninsured (aOR: 22.32, 95% CI: 4.26-116.94, p < 0.001), shock (aOR: 10.57, 95% CI: 1.41-79.09, p = 0.022), mechanical ventilation (aOR: 75.29, 95% CI: 12.37-458.28, p < 0.001), and hypertension (aOR: 4.34, 95% CI: 1.37-13.82, p = 0.013) were independent risk factors of in-hospital mortality of HC patients. Besides, high CCI was an independent risk factor for higher ICU Admission (aOR: 5.91, 95% CI: 2.31-15.08, p < 0.001), hypoglycemia (aOR: 2.19, 95% CI:1.01-4.08, p = 0.049), longer LOS (aOR: 1.23, 95% CI: 1.19-2.27, p = 0.021), and higher hospitalisation expense (aOR: 2089.97, 95% CI: 193.33-3988.61, p = 0.031) of HC patients. CONCLUSION: CCI is associated with in-hospital mortality, ICU admission, hypoglycemia, LOS, and hospitalisation expense of HC patients. CCI could be an ideal indicator to identify, monitor, and manage chronic comorbidities among HC patients.

Comorbidity burden and outcomes after mechanical thrombectomy for large vessel occlusion: A retrospective analysis.

OBJECTIVES: Patients with acute ischemic stroke (AIS) often have an accumulation of pre-existing comorbidities, but its clinical impact on outcomes after mechanical thrombectomy (MT) remains unknown. Therefore, we examined whether comorbidity burden before AIS onset could predict clinical outcomes after MT. METHODS: In this retrospective cohort, we enrolled consecutive patients with community-onset AIS who underwent MT between April 2016 and December 2021. To evaluate each patient's comorbidity burden, we calculated Charlson comorbidity index (CCI), then classified the patients into the High CCI (≥ 3) and the Low CCI (< 3) groups. The primary outcome was a good neurological outcome at 90 days, defined as a modified Rankin scale 0-2 or no worse than the previous daily conditions. All-cause mortality at 90 days and hemorrhagic complications after MT were also compared between the two groups. We estimated the odds ratios and their confidence intervals using a multivariable logistic regression model. RESULTS: A total of 388 patients were enrolled, of whom 86 (22.2%) were classified into the High CCI group. Patients in the High CCI group were less likely to achieve a good neurological outcome (adjusted odds ratio of 0.26 [95% confidence interval, 0.12-0.58]). Moreover, symptomatic intracranial hemorrhage was more common in the High CCI (14.0% vs. 4.6%; adjusted odds ratio, 4.10 [95% confidence interval, 1.62-10.3]). CONCLUSIONS: Comorbidity burden assessed by CCI was associated with clinical outcomes after MT. CCI has the potential to become a simple and valuable tool for predicting neurological prognosis among patients with AIS and MT.